Inicio  /  Aerospace  /  Vol: 10 Par: 3 (2023)  /  Artículo
ARTÍCULO
TITULO

Uncertainty Quantification of Compressor Map Using the Monte Carlo Approach Accelerated by an Adjoint-Based Nonlinear Method

Shenren Xu    
Qian Zhang    
Dingxi Wang and Xiuquan Huang    

Resumen

Precise and inexpensive uncertainty quantification (UQ) is crucial for robust optimization of compressor blades and to control manufacturing tolerances. This study looks into the suitability of MC-adj-nonlinear, a nonlinear adjoint-based approach, to precisely and rapidly assess the performance discrepancies of a transonic compressor blade section, arising from geometric alterations, and building upon previous research. In order to assess the practicality and illustrate the benefits of the adjoint-based nonlinear approach, its proficiency and precision are gauged against two other methodologies, the adjoint-based linear approach (MC-adj-linear) and the high-fidelity nonlinear Computational Fluid Dynamics (MC-CFD) method. The MC-adj-nonlinear methodology exhibits impressive generalization capabilities. The MC-adj-nonlinear method offers a great balance between precision and time efficiency, since it is more precise than the MC-adj-linear method in both design and near-stall conditions, yet requires approximately a thirtieth of the time of the MC-CFD method. Finally, the MC-adj-nonlinear method was utilized to conduct fast UQ analyses of the section at four distinct speeds to quantify the performance uncertainty for the compressor map. It is found that aerodynamic performance is more sensitive to geometric deviations at high speeds than at low speeds. The impact of the geometric deviations is generally detrimental to the mean efficiency.

 Artículos similares

       
 
Haohao Wang, Limin Gao and Baohai Wu    
Many probability-based uncertainty quantification (UQ) schemes require a large amount of sampled data to build credible probability density function (PDF) models for uncertain parameters. Unfortunately, the amounts of data collected as to compressor blad... ver más
Revista: Aerospace

 
Mingzhi Li, Xianjun Yu, Dejun Meng, Guangfeng An and Baojie Liu    
Studies on the geometry variation-related compressor uncertainty quantification (UQ) have often used dimension reduction methods, such as the principal component analysis (PCA), for the modeling of deviations. However, in the PCA method, the main eigenmo... ver más
Revista: Aerospace

 
Vladimir Ulansky and Ahmed Raza    
The operable state of a system is maintained during operation, which requires knowledge of the system?s state. Technical diagnostics, as a process of accurately obtaining information about the system state, becomes a crucial stage in the life cycle of an... ver más
Revista: Aerospace

 
Wenhao Fu, Zeshuai Chen and Jiaqi Luo    
Stochastic variations of the operation conditions and the resultant variations of the aerodynamic performance in Low-Pressure Turbine (LPT) can often be found. This paper studies the aerodynamic performance impact of the uncertain variations of flow para... ver más
Revista: Aerospace

 
Nikhil Iyengar, Dushhyanth Rajaram and Dimitri Mavris    
Uncertainties in the atmosphere and flight conditions can drastically impact the performance of an aircraft and result in certification delays. However, uncertainty propagation in high-fidelity simulations, which have become integral to the design proces... ver más
Revista: Aerospace